Bayesian Inference for Causal Networks R package baycn version 2.0.0 CRAN Task View: Bayesian (https://CRAN.R-project.org/view=Bayesian) An approximate Bayesian method for inferring Directed Acyclic Graphs (DAGs) for continuous, discrete, and mixed data. The algorithm can use the graph inferred by another more efficient graph inference method as input; the input graph may contain false edges or undirected edges but can help reduce the search space to a more manageable size. A Metropolis-Hastings-like sampling algorithm is then used to infer the posterior probabilities of edge direction and edge absence. References: Martin, Patchigolla and Fu (2026) <doi:10.48550/arXiv.1909.10678>. Software Depends: R (>= 3.5.0) Imports: egg, ggplot2, igraph, MASS, methods, expm Suggests: testthat Audrey Fu <audreyqyfu@gmail.com> Comprehensive R Archive Network (CRAN) Evan A Martin [aut], Venkata Patchigolla [ctb], Audrey Fu [aut, cre] GPL-3 file LICENSE (https://CRAN.R-project.org/package=baycn/LICENSE) 2026-03-10 application/tgz https://CRAN.R-project.org/package=baycn doi:10.32614/CRAN.package.baycn